Hypoperfusion Intensity Ratio as an Indirect Imaging Surrogate in Patients With Anterior Circulation Large-Vessel

Omar Hamam1, Julie Gudenkauf2, Rawan Moustafa3,4

  • 1Department of Radiology, Massachusetts General Hospital Harvard Medical School Boston MA.

Insights

Poor collateral status in acute ischemic stroke patients is linked to cardioembolic/cryptogenic causes, higher NIH Stroke Scale scores, and male sex. This finding aids in predicting stroke outcomes and guiding treatment decisions.

Area of Science:

  • Neurology
  • Radiology
  • Stroke Medicine

Background:

  • Collateral status (CS) is vital for infarct progression, hemorrhage risk, and outcomes in acute ischemic stroke (AIS) with large-vessel occlusions (LVOs).
  • Hypoperfusion intensity ratio (HIR) is a validated noninvasive imaging biomarker for assessing CS.
  • Admission laboratory findings can also impact AIS-LVO patient outcomes.

Purpose of the Study:

  • To investigate the relationship between admission laboratory findings, baseline characteristics, and collateral status (CS) in AIS-LVO patients.
  • To assess CS using the hypoperfusion intensity ratio (HIR) derived from computed tomography perfusion.
  • To identify predictors of poor CS in this patient cohort.

Main Methods:

  • Retrospective analysis of 221 AIS-LVO patients undergoing pretreatment computed tomography perfusion.
  • HIR calculated using RAPID software.
  • Binary and multivariable logistic regression models employed to determine associations with poor CS.

Main Results:

  • Patients with AIS due to cardioembolic/cryptogenic causes showed a higher likelihood of poor CS (aOR, 2.67).
  • Higher admission National Institutes of Health Stroke Scale (NIHSS) scores (≥12) were significantly associated with poor CS (aOR, 3.12).
  • Male sex was also independently associated with poor CS (aOR, 2.06).

Conclusions:

  • Cardioembolic or cryptogenic stroke etiology, NIHSS score ≥12, and male sex are significant predictors of poor CS in AIS-LVO.
  • These factors, identified via HIR, can help stratify patient risk and inform treatment strategies.
  • Further research may explore the interplay of laboratory findings and CS in AIS-LVO.
Abstract